As an Machine Learning Engineer, you are responsible for:
- Design and implement MLOps infrastructure so teams can experiment fast and ship with confidence.
- Build tooling for model versioning, evaluation, monitoring and feedback loops.
- Introduce "think like a scientist" processes — structured experimentation, reproducibility, clear decision frameworks.
- Automate LLM prompt pipelines and integrate them safely and reliably into production systems.
- Drive best practices for model lifecycle management, performance, and monitoring in production.
- Mentor peers in MLOps and engineering best practices; advocate for cross-functional collaboration.
Job Qualifications
Qualifications, Skills and Experience
- Strong Python engineering skills, with experience developing production-ready applications, services, or ML solutions.
- Broad experience in Machine Learning Engineering, including developing, deploying, and maintaining machine learning solutions.
- Hands-on experience building data and ML pipelines using modern workflow or orchestration frameworks.
- Good understanding of software engineering best practices, including version control, testing, and code quality.
- Experience working with ML workflows from development through deployment and production support.
- Experience with MLOps or LLMOps libraries, tools, and workflows.
- Familiarity with model monitoring, experiment tracking, and ML-focused CI/CD practices.
- Experience working with AWS or GCP data and compute services.
- Experience with containerisation technologies such as Docker.
- Familiarity with Infrastructure as Code (IaC) tools and practices.
- Exposure to deploying and maintaining machine learning models in production environments.
Job Overview
Company BEEPO, INC.
Employment Type Full-Time
Experience 2-3 Years
Personnel Needed 1 Open
Category IT & Software
Services Software Development, AI Automation, Python
Location Beepo Inc 2nd floor Business Center 9 Philexcel Business Park MA Roxas Hiway CFZ Pamp